Title
Robust distributed cooperative RSS-based localization for directed graphs in mixed LoS/NLoS environments.
Abstract
The accurate and low-cost localization of sensors using a wireless sensor network is critically required in a wide range of today’s applications. We propose a novel, robust maximum likelihood-type method for distributed cooperative received signal strength-based localization in wireless sensor networks. To cope with mixed LoS/NLoS conditions, we model the measurements using a two-component Gaussian mixture model. The relevant channel parameters, including the reference path loss, the path loss exponent, and the variance of the measurement error, for both LoS and NLoS conditions, are assumed to be unknown deterministic parameters and are adaptively estimated. Unlike existing algorithms, the proposed method naturally takes into account the (possible) asymmetry of links between nodes. The proposed approach has a communication overhead upper-bounded by a quadratic function of the number of nodes and computational complexity scaling linearly with it. The convergence of the proposed method is guaranteed for compatible network graphs, and compatibility can be tested a priori by restating the problem as a graph coloring problem. Simulation results, carried out in comparison to a centralized benchmark algorithm, demonstrate the good overall performance and high robustness in mixed LoS/NLoS environments.
Year
DOI
Venue
2019
10.1186/s13638-018-1335-7
EURASIP Journal on Wireless Communications and Networking
Keywords
Field
DocType
Cooperative localization, Received signal strength (RSS), Maximum likelihood estimation, Wireless sensor network (WSN)
Non-line-of-sight propagation,Computer science,Computer network,Directed graph,Robustness (computer science),Real-time computing,Path loss,Wireless sensor network,Mixture model,Graph coloring,Computational complexity theory
Journal
Volume
Issue
ISSN
2019
1
1687-1499
Citations 
PageRank 
References 
3
0.42
24
Authors
4
Name
Order
Citations
PageRank
Luca Carlino131.10
Di Jin2193.07
Michael Muma314419.51
Abdelhak M. Zoubir41036148.03